Mechanical Performance and Durability of Date Palm Fibers Repair Mortar
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Concrete is the most widely used material in the world after water. However, concrete could be damaged under aggressive environments and many concrete structures require repair and frequent maintenance. Readymade mortars with and without synthetic fibers such as polypropylene and acrylic are often used as repair mortars. The partial replacement of cement by supplementary cementitious materials and the use of alternative fibers such as natural and agro-waste fibers could reduce the environmental impact of readymade mortars. Methods: This paper presents a comparative study between the performance of laboratory made and ready-made repair mortars. The laboratory repair mortars were based on date palm fibers and local mineral additions (slag and natural pozzolan). The volume ratio of date palm fibers addition was 0.75% and mineral additions content were fixed at 15% as cement replacement. Compressive strength, flexural strength, shrinkage and the bond strength by slant shear test and tensile strength of concrete by the pull-off method were investigated. The durability of the mortar was evaluated by water capillary absorption. Results: The results indicated that the addition of natural fibers and the substitution of cement by 15% of mineral additions improves the flexural strength but reduces the compressive strength of the fiber-reinforced repair mortar. The lowest values of total shrinkage, water capillary absorption and sorptivity were observed for repair mortars based on acrylic fibers compared to repair mortars with natural vegetables fibers. Conclusion: The mechanical and durability performances of laboratory made repair mortars were comparable to those of readymade mortars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it